11+ Voice recognition Jobs in Bangalore (Bengaluru) | Voice recognition Job openings in Bangalore (Bengaluru)

• Your responsibilities:
• Build, improve and extend NLP capabilities
• Research and evaluate different approaches to NLP problems
• Must be able to write code that is well designed, produce deliverable results
• Write code that scales and can be deployed to production

• Fundamentals of statistical methods is a must
• Experience in named entity recognition, POS Tagging, Lemmatization, vector representations of textual data and neural networks - RNN, LSTM
• A solid foundation in Python, data structures, algorithms, and general software development skills.
• Ability to apply machine learning to problems that deal with language
• Engineering ability to build robustly scalable pipelines
• Ability to work in a multi-disciplinary team with a strong product focus

Job Title – Data Scientist (Forecasting)

Anicca Data is seeking a Data Scientist (Forecasting) who is motivated to apply his/her/their skill set to solve complex and challenging problems. The focus of the role will center around applying deep learning models to real-world applications.  The candidate should have experience in training, testing deep learning architectures.  This candidate is expected to work on existing codebases or write an optimized codebase at Anicca Data. The ideal addition to our team is self-motivated, highly organized, and a team player who thrives in a fast-paced environment with the ability to learn quickly and work independently.

Job Location: Remote (for time being) and Bangalore, India (post-COVID crisis)

• At least 3+ years of experience in a Data Scientist role
• Bachelor's/Master’s degree in Computer Science, Engineering, Statistics, Mathematics, or similar quantitative discipline. D. will add merit to the application process
• Experience with large data sets, big data, and analytics
• Exposure to statistical modeling, forecasting, and machine learning. Deep theoretical and practical knowledge of deep learning, machine learning, statistics, probability, time series forecasting
• Training Machine Learning (ML) algorithms in areas of forecasting and prediction
• Experience in developing and deploying machine learning solutions in a cloud environment (AWS, Azure, Google Cloud) for production systems
• Research and enhance existing in-house, open-source models, integrate innovative techniques, or create new algorithms to solve complex business problems
• Experience in translating business needs into problem statements, prototypes, and minimum viable products
• Experience managing complex projects including scoping, requirements gathering, resource estimations, sprint planning, and management of internal and external communication and resources
• Write C++ and Python code along with TensorFlow, PyTorch to build and enhance the platform that is used for training ML models

Preferred Experience

• Worked on forecasting projects – both classical and ML models
• Experience with training time series forecasting methods like Moving Average (MA) and Autoregressive Integrated Moving Average (ARIMA) with Neural Networks (NN) models as Feed-forward NN and Nonlinear Autoregressive
• Strong background in forecasting accuracy drivers
• Experience in Advanced Analytics techniques such as regression, classification, and clustering
• Ability to explain complex topics in simple terms, ability to explain use cases and tell stories

Job Description 

Data scientist with strong background in data mining, machine learning, recommendation systems, and statistics. Should possess signature strengths of a qualified mathematician with ability to apply concepts of Mathematics, Applied Statistics, with specialization in one or more of NLP, Computer Vision, Speech, Data mining to develop models that provide effective solution.. A strong data engineering background with hands-on coding capabilities is needed to own and deliver outcomes. 

A Master’s or PhD Degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent experience, 7+ years of industry experience in predictive modelling, data science and analysis, with prior experience in a ML or data scientist role and a track record of building ML or DL models. 

Responsibilities and skills: 

● Work with our customers to deliver a ML / DL project from beginning to end, including understanding the business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models to deliver business impact to the organization. 

● Selecting features, building and optimizing classifiers using ML techniques ● Data mining using state-of-the-art methods, create text mining pipelines to clean & process large unstructured datasets to reveal high quality information and hidden insights using machine learning techniques 

● Should be able to appreciate and work on Computer Vision problems – for example extract rich information from images to categorize and process visual data— Develop machine learning algorithms for object and image classification, Experience in using DBScan, PCA, Random Forests and Multinomial Logistic Regression to select the best features to classify objects. 

OR 

● Deep understanding of NLP such as fundamentals of information retrieval, deep learning approaches, transformers, attention models, text summarisation, attribute extraction, etc. Preferable experience in one or more of the following areas: recommender systems, moderation of user generated content, sentiment analysis, etc. 

OR 

● Speech recognition, speech to text and vice versa, understanding NLP and IR, text summarisation, statistical and deep learning approaches to text processing. Experience of having worked in these areas.

Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc. Needs to appreciate deep learning frameworks like MXNet, Caffe 2, Keras, Tensorflow 

● Experience in working with GPUs to develop models, handling terabyte size datasets ● Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, mlr, mllib, Scikit-learn, caret etc - excellence in at least one of these is highly desirable ● Should be able to work hands-on in Python, R etc. Should closely collaborate & work with engineering teams to iteratively analyse data using Scala, Spark, Hadoop, Kafka, Storm etc., 

● Experience with NoSQL databases and familiarity with data visualization tools will be of great advantage

About Kloud9:

Kloud9 exists with the sole purpose of providing cloud expertise to the retail industry. Our team of cloud architects, engineers and developers help retailers launch a successful cloud initiative so you can quickly realise the benefits of cloud technology. Our standardised, proven cloud adoption methodologies reduce the cloud adoption time and effort so you can directly benefit from lower migration costs.

Kloud9 was founded with the vision of bridging the gap between E-commerce and cloud. The E-commerce of any industry is limiting and poses a huge challenge in terms of the finances spent on physical data structures.

At Kloud9, we know migrating to the cloud is the single most significant technology shift your company faces today. We are your trusted advisors in transformation and are determined to build a deep partnership along the way. Our cloud and retail experts will ease your transition to the cloud.

Our sole focus is to provide cloud expertise to retail industry giving our clients the empowerment that will take their business to the next level. Our team of proficient architects, engineers and developers have been designing, building and implementing solutions for retailers for an average of more than 20 years.

We are a cloud vendor that is both platform and technology independent. Our vendor independence not just provides us with a unique perspective into the cloud market but also ensures that we deliver the cloud solutions available that best meet our clients' requirements.

Responsibilities:

●       Studying, transforming, and converting data science prototypes

●       Deploying models to production

●       Training and retraining models as needed

●       Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their respective scores

●       Analyzing the errors of the model and designing strategies to overcome them

●       Identifying differences in data distribution that could affect model performance in real-world situations

●       Performing statistical analysis and using results to improve models

●       Supervising the data acquisition process if more data is needed

●       Defining data augmentation pipelines

●       Defining the pre-processing or feature engineering to be done on a given dataset

●       To extend and enrich existing ML frameworks and libraries

●       Understanding when the findings can be applied to business decisions

●       Documenting machine learning processes

Basic requirements: 

●       4+ years of IT experience in which at least 2+ years of relevant experience primarily in converting data science prototypes and deploying models to production

●       Proficiency with Python and machine learning libraries such as scikit-learn, matplotlib, seaborn and pandas

●       Knowledge of Big Data frameworks like Hadoop, Spark, Pig, Hive, Flume, etc

●       Experience in working with ML frameworks like TensorFlow, Keras, OpenCV

●       Strong written and verbal communications

●       Excellent interpersonal and collaboration skills.

●       Expertise in visualizing and manipulating big datasets

●       Familiarity with Linux

●       Ability to select hardware to run an ML model with the required latency

●       Robust data modelling and data architecture skills.

●       Advanced degree in Computer Science/Math/Statistics or a related discipline.

●       Advanced Math and Statistics skills (linear algebra, calculus, Bayesian statistics, mean, median, variance, etc.)

Nice to have

●       Familiarity with Java, and R code writing.

●       Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world

●       Verifying data quality, and/or ensuring it via data cleaning

●       Supervising the data acquisition process if more data is needed

●       Finding available datasets online that could be used for training

Why Explore a Career at Kloud9:

With job opportunities in prime locations of US, London, Poland and Bengaluru, we help build your career paths in cutting edge technologies of AI, Machine Learning and Data Science. Be part of an inclusive and diverse workforce that's changing the face of retail technology with their creativity and innovative solutions. Our vested interest in our employees translates to deliver the best products and solutions to our customers.

• Research and develop statistical learning models for data analysis
• Collaborate with product management and engineering departments to understand company needs and devise possible solutions
• Keep up-to-date with latest technology trends
• Communicate results and ideas to key decision makers
• Implement new statistical or other mathematical methodologies as needed for specific models or analysis
• Optimize joint development efforts through appropriate database use and project design

Qualifications/Requirements:

• Masters or PhD in Computer Science, Electrical Engineering, Statistics, Applied Math or equivalent fields with strong mathematical background
• Excellent understanding of machine learning techniques and algorithms, including clustering, anomaly detection, optimization, neural network etc
• 3+ years experiences building data science-driven solutions including data collection, feature selection, model training, post-deployment validation
• Strong hands-on coding skills (preferably in Python) processing large-scale data set and developing machine learning models
• Familiar with one or more machine learning or statistical modeling tools such as Numpy, ScikitLearn, MLlib, Tensorflow
• Good team worker with excellent communication skills written, verbal and presentation

Desired Experience:

• Experience with AWS, S3, Flink, Spark, Kafka, Elastic Search
• Knowledge and experience with NLP technology
• Previous work in a start-up environment

• B.Tech/MTech from tier 1 institution
• 8+years of experience in machine learning techniques like logistic regression, random forest, boosting, trees, neural networks, etc.
• Showcased experience with Python, SQL and proficiency in Scikit Learn, Pandas, NumPy, Keras and TensorFlow/pytorch
• Experience of working with Qlik sense or Tableau is a plus